The present invention relates to imaging devices, and more particularly, to a computer mouse or a digital camera for capturing and analyzing images.
Many devices capture images as digitized electronic signals (representing the captured image) and analyze the digitized electronic signals (“image data”) for various purposes. For example, quality control inspection systems capture images of parts under inspection and analyzes the image data to identify various features of the images data such as the size of the parts and imperfections, if any. Another example is an optical computer mouse which captures a sequence of images for analyzing. The optical computer mouse, to determine navigation or movement information, analyzes the image data from each captured image to identify various features within the captured image, then compares the relative location of the identified features between different images to determine the movement information.
A first type of the optical computer mouse typically operates on a relatively smooth surface (to facilitate easy gliding movement), the operating surface having relatively small features. For convenience, this type of optical computer mouse is referred to as a 2D optical computer mouse. For example, a 2D optical computer mouse may operate on a piece of blank paper. To determine movement information, the 2D optical computer mouse needs to capture and identify the small features (for example, paper fiber) of the surface on which it is operating. To assist in capturing these small features, the 2D optical computer mouse commonly includes a light source such as an LED (light emitting diode) shining light (incident light) on an imaging area (of the underlying surface) under the optical computer mouse.
The light from the LED is introduced at a grazing angle to cast shadows on small features of the imaging area under the 2D optical computer mouse (thus imaging a portion of the underlying surface) and to reflect off of the imaging area. The reflected light is captured by an image sensor within the 2D optical computer mouse and converted to image data (including the light and shadow areas). The image data is analyzed by a processor which is configured to detect features of the image data. During the analysis, background data are often referred to as the noise (N) and the detected feature data are often referred to as the signal (S). A high signal-to-noise (S/N)-ratio is preferred because it is easier to detect features hence require less hardware and software resources.
A second type of the optical computer mouse typically operates as a 3D mouse and is held and freely waved about. The 3D optical computer mouse captures a sequence of random or unpredictable images and processes image data from the captured images to provide navigation or movement information. During its movement, the 3D optical computer mouse captures a sequence of images that it is exposed to, for example, a wall or other scenes, indoor or outdoor. For such a device, depending on the environment to which it is exposed, the captured images may be faint with minimal distinguishable features with which the movement information can be determined. That is, depending on the images to which 3D optical computer mouse is exposed, the S/N ratio can be lower than desired.
For both types of the optical computer mouse, it can be difficult to capture small features, distinguish faint features, or both due to relatively low S/N ratio. To increase the S/N ratio, brighter incident light, more sensitive image sensors, or both can be used; however, these components increase cost and operating expenses as well as to decrease reliability.
Accordingly, there remains a need for an improved method and apparatus for capturing images to improve the S/N ratio of captured images.